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The Metabolic Regimes of Flowing Waters

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The Metabolic Regimes of Flowing Waters LIMNOLOGY and Limnol. Oceanogr. 63, 2018, S99–S118 VC 2017 The Authors Limnology and Oceanography published by Wiley Periodicals, Inc. OCEANOGRAPHY on behalf of Association for the Sciences of Limnology and Oceanography doi: 10.1002/lno.10726 The metabolic regimes of flowing waters E. S. Bernhardt ,1* J. B. Heffernan ,2 N. B. Grimm ,3 E. H. Stanley ,4 J. W. Harvey ,5 M. Arroita,6,7 A. P. Appling,8 M. J. Cohen,9 W. H. McDowell ,10 R. O. Hall, Jr.,7,a J. S. Read,11 B. J. Roberts,12 E. G. Stets,13 C. B. Yackulic14 1Department of Biology, Duke University, Durham, North Carolina 2Nicholas School of the Environment, Duke University, Durham, North Carolina 3Arizona State University, Tempe, Arizona 4Center for Limnology, University of Wisconsin, Madison, Wisconsin 5National Research Program, U.S. Geological Survey, Reston, Virginia 6Department of Plant Biology and Ecology, University of the Basque Country, Bilbao, Spain 7Department of Zoology and Physiology, University of Wyoming, Laramie, Wyoming 8US Geological Survey, Office of Water Information, Tucson, Arizona 9School of Forest Resources and Conservation, University of Florida, Gainesville, Florida 10Department of Natural Resources and the Environment, University of New Hampshire, Durham, New Hampshire 11U.S. Geological Survey, Office of Water Information, Middleton, Wisconsin 12Louisiana Universities Marine Consortium, Chauvin, Louisiana 13U.S. Geological Survey, National Research Program, Boulder, Colorado 14U.S. Geological Survey, Southwest Biological Science Center, Flagstaff, Arizona Abstract The processes and biomass that characterize any ecosystem are fundamentally constrained by the total amount of energy that is either fixed within or delivered across its boundaries. Ultimately, ecosystems may be understood and classified by their rates of total and net productivity and by the seasonal patterns of pho- tosynthesis and respiration. Such understanding is well developed for terrestrial and lentic ecosystems but our understanding of ecosystem phenology has lagged well behind for rivers. The proliferation of reliable and inexpensive sensors for monitoring dissolved oxygen and carbon dioxide is underpinning a revolution in our understanding of the ecosystem energetics of rivers. Here, we synthesize our current understanding of the drivers and constraints on river metabolism, and set out a research agenda aimed at characterizing, classi- fying and modeling the current and future metabolic regimes of flowing waters. The fuel that powers almost all of Earth’s ecosystems is autotrophs and heterotrophs) is measured as ecosystem res- created by organisms capable of the alchemy of photosyn- piration (ER). Together, GPP and ER are the fundamental thesis, in which solar energy, water, and carbon dioxide are metabolic rates of ecosystems that constrain the energy sup- converted into reduced carbon compounds that are then ply and energy dissipation through food chains, and the bal- used to sustain life. We measure this conversion of solar ance of these two fluxes, measured as net ecosystem energy into organic energy as the gross primary productivity production (NEP), determines whether carbon accumulates (GPP) of ecosystems. The collective dissipation of this or is depleted within an ecosystem. Terrestrial ecosystems organic energy through organismal metabolism (of both often have predictable annual cycles, with both GPP and NEP typically peaking during warmer and wetter months of the year. In many well-studied lakes productivity peaks *Correspondence: [email protected] when warming temperatures, lengthening days, and high aPresent address: Flathead Lake Biological Station, University of Montana, nutrient concentrations occur in concert. The life cycles of Polson, Montana many consumers are likely synchronized to these seasonal oscillations such that periods of peak energetic demand by This is an open access article under the terms of the Creative Commons consumers coincide with or follow the peak productivity of Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly their preferred plant or prey (e.g., Lampert et al. 1986; Berger cited and is not used for commercial purposes. et al. 2010). As a result, ecosystem respiration tends to S99 Bernhardt et al. Metabolic regimes Fig. 1. Temporal trends in dissolved oxygen (DO shown as % of atmospheric saturation) for four contrasting U.S. rivers over a 4-yr period. High diel variation in dissolved oxygen is a proxy for high ecosystem GPP. The top trace is from the Menominee River in northern, Wisconsin, a large river with clear summer peaks and winter lows in stream metabolism. Dissolved oxygen traces for the more southern Five Mile Creek in Alabama and San Anoto- nio River in Texas show little seasonality, with the smaller Creek having sustained high diel variation in DO and the more urban river having many alternating periods of high and low diel DO variation. The bottom trace is from Fanno Creek, a heavily shaded and frequently flooded small stream in western Oregon. Data from each of these four streams appears again (along with axes labels) in Figs. 3, 5. Here, we remove axes scores to focus on the differences in seasonality of a common signal across streams. The scale of both axes is the same for all four series. covary with GPP. This phenology of the ecosystem, or its reduced coherence between climate drivers and river ecosys- seasonal timing of carbon, water and energy exchange (sensu tem productivity and respiration. Noormets 2009) is both a cause and a consequence of the Of course, the relative importance of terrestrial shading phenology of all component organisms. and terrestrial organic matter inputs varies with river size The same “cause and consequence of organism (Vannote et al. 1980). Just as the importance of terrestrial phenology” argument cannot be made for river ecosystems inputs of nutrients and organic matter to lake food webs for three reasons. First, in many rivers seasonal variation in diminishes as the ratio of lake size to watershed size light is uncorrelated with seasonal variation in temperature, increases (Tanentzap et al. 2017), we expect that the relative because of the reduction in light supply due to canopy inter- importance of canopy shading, allochthonous inputs, and ception, sediment loads or colored organic matter. Second, hydrologic disturbance should decline between headwater in many rivers intense and frequent high flow events regu- streams and large rivers. This gradient in river size impacts larly reduce the biomass of autotrophs (algae, mosses, and the expected ecosystem phenology, with well-lit and less fre- macrophytes) through scouring or burial while stream drying quently disturbed large rivers having regular summer pro- can strand and desiccate autotrophs on the channel bed. ductivity peaks while shaded headwaters with frequent Finally, most rivers receive energetic subsidies in the form of flooding are likely to have productivity peaks that are mis- detritus and dissolved organic matter from their surrounding matched to the terrestrial growing season (Fig. 1). These pre- watersheds. These allochthonous inputs can match or exceed dicted longitudinal patterns can be obscured for rivers with in situ GPP and thus decouple the seasonal and annual pat- high sediment or colored organic matter inputs. Because the terns of GPP and ER. For each of these reasons we expect a temporal signals of GPP and ER are so diverse across streams S100 Bernhardt et al. Metabolic regimes and years, and so often asynchronous with terrestrial pro- in the concentration of dissolved oxygen (DO) throughout a ductivity and climate drivers, we propose that the term meta- diel (24-h) cycle, using increases during daylight hours and bolic regimes is more appropriate than phenology to describe overnight declines to calculate rates of GPP, ER, and NEP. In these patterns. Here, we define a metabolic regime as the Odum’s initial metabolism estimates (Odum 1956, 1957) characteristic temporal pattern of ecosystem GPP and ER these changes were documented by collecting samples at 2– observed for a river. 4 h intervals throughout a day followed by manual analysis Despite the frequent mismatches in the timing of peak of DO concentration via titration. Sampling around the energy supply, thermal optima, and disturbance river ecosys- clock by this method is labor intensive, and the duration of tems support a tremendous diversity of species (Strayer and early studies was thus limited to a handful of days during Dudgeon 2010) and can convert enormous quantities of the year. Later efforts were enabled by instantaneous meas- organic matter and inorganic nutrients into CO2,CH4,N2, urements of DO with first generation environmental sensors. and N2O gases (Cole et al. 2007; Mulholland et al. 2008; Bat- Because these sensors were expensive and required frequent tin et al. 2009; Raymond et al. 2013; Stanley et al. 2016). calibration, researchers tended to deploy them for very lim- The capacity of rivers to support these critical functions ited periods of time. As a result, most reported rates of river depends, fundamentally, on ecosystem metabolism, defined ecosystem metabolism were derived from a small number of as “the production and destruction of organic matter, and the measurement days over a year (e.g., 2–12 d; synthesized by associated fluxes of nutrients, through the gross photosynthetic Lamberti and Steinman 1997; Finlay 2011). These brief sam- and respiratory
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